Project Summary Many hospital patients, particularly older patients, are dependent on staff for assistance with activities of daily living (ADL) such as walking and toileting. Assistance with these activities is time-consuming for staff, and evidence suggests that ADL assistance is not consistently provided in hospitals. This inconsistent ADL care is often associated with adverse events, particularly falls, with 30-60% of hospital falls related to patients? attempts to use the bathroom. There is evidence that consistent toileting and mobility assistance can prevent falls, but barriers related to staffing and the complex hospital work environment make it difficult to provide this care consistently in daily acute care practice. The National Academy of Medicine has identified a systems-engineering approach called Discrete Event Simulation (DES) as a method to improve the quality and efficiency of health care. This approach has been used for decades in other industries and more recently applied to healthcare settings. Discrete Event Simulation mathematically models multiple work parameters that define a care setting, such as the time to provide an episode of care, and predicts the ability of staff within that setting to provide care at different points in time based on other competing demands and care requirements. Sensitivity and predictive analyses can be used to examine how changes to the system, such as different staff schedules or order of care routines, affect and improve care delivery thus facilitating more efficient management. This investigative team has applied DES to the nursing home setting to identify staffing needs to provide care based on a range of resident ADL dependencies and staffing resources. However, this DES methodology has not been applied to the acute care setting, where many older patients need similar ADL care services and also are at risk for falls. Thus, the purpose of the proposed study is to apply DES to the hospital setting focused on units that care for large numbers of older patients with ADL dependencies. This study will produce a novel technology that hospital providers may use to efficiently manage medical units by experimenting with innovative approaches to improve ADL care prior to more expensive efforts to implement and test interventions in actual practice. This technology will be first developed and tested in an Acute Care for the Elderly (ACE) unit. However, the degree to which the model accurately describes care in two other diverse hospital units will be tested in preparation for disseminating the model to other units and hospitals via a web-based simulation tool.